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Abstract:

A method and system are provided for conserving network resources such as
battery power of a battery-powered communication device used to support a
conversation over a wireless network transport media. Periods of silence
are detected during conversation taking place on a network having
controllable resources such as battery power. Using the periods of
silence so-detected, future silence periods occurring on the network are
then predicted. Allocation of at least a portion of the controllable
resources is controlled based on the future silence periods so-predicted.

Claims:

1. A method of conserving battery power when using a battery-powered
communication device to support a conversation over a wireless network
transport media, comprising the steps of: providing a battery-powered
communication device capable of supporting a conversation over a wireless
network transport media, the communication device having a high power
state (HPS) of operation and a low power state (LPS) of operation wherein
battery power required for said LPS is less than battery power required
for said HPS; detecting periods of silence during at least a portion of
at least one conversation supported by the communication device;
predicting, using said periods of silence so-detected, future silence
periods occurring during at least one of (i) a remainder of said at least
one conversation, and (ii) a future conversation supported by the
communication device; and placing the communication device in said LPS
during each of said future silence periods so-predicted.

2. A method according to claim 1, wherein the conversation is packetized.

3. A method according to claim 1, wherein said portion of at least one
conversation is in the form of digitized samples thereof, and wherein
said step of detecting comprises the steps of: selecting a threshold
audio level; and comparing said threshold audio level to an average audio
level associated with a portion of said digitized samples, wherein one of
said periods of silence is indicated each time said average audio level
is less than said threshold audio level.

4. A method according to claim 1, wherein said step of predicting
comprises the steps of: generating an empirical cumulative distribution
function (ECDF) using said periods of silence so-detected; generating a
computed training silence length of time α using said ECDF;
detecting a current silence period occurring during one of (i) said
remainder of said at least one conversation, and (ii) said future
conversation; and determining, using said ECDF, a conditional probability
that said current silence period will last an additional length of time
Δ beyond said computed training silence length of time α,
wherein one of said future silence periods is defined by
(α+Δ) when said conditional probability is greater than or
equal to a threshold probability β.

5. A method according to claim 4, wherein said threshold probability
β is in the range of approximately 0.25 to approximately 0.7.

6. A method according to claim 4 wherein, when said conditional
probability is greater than or equal to said threshold probability
β, said step of determining is repeated until said additional length
of time Δ is maximized.

7. A method according to claim 4 wherein, when said conditional
probability is less than said threshold probability β, said method
further comprises the step of setting said one of said future silence
periods equal to said computed training silence length of time α.

8. A method of conserving battery power when using a battery-powered
communication device to support a conversation over a wireless network
transport media, comprising the steps of: providing a battery-powered
communication device capable of supporting a conversation over a wireless
network transport media, the communication device having a high power
state (HPS) of operation and a low power state (LPS) of operation wherein
battery power required for said LPS is less than battery power required
for said HPS; selecting a threshold audio level; comparing said threshold
audio level to an average audio level of a portion of digitized samples
associated with a portion of at least one conversation supported by the
communication device, wherein periods of silence are indicated each time
said average audio level is less than said threshold audio level;
generating an empirical cumulative distribution function (ECDF) using
said periods of silence so-indicated during said step of comparing;
generating a computed training silence length of time α using said
ECDF; detecting a current silence period occurring during one of (i) a
remainder of said at least one conversation, and (ii) a future
conversation supported by the communication device; determining, using
said ECDF, a conditional probability that said current silence period
will last an additional length of time Δ beyond said computed
training silence length of time α, wherein a length of a future
silence period is defined by (α+Δ) when said conditional
probability is greater than or equal to a threshold probability β;
and placing the communication device in said LPS during said future
silence period so-defined during said step of determining.

9. A method according to claim 8, wherein the conversation is packetized.

10. A method according to claim 8, wherein said threshold probability
β is in the range of approximately 0.25 to approximately 0.7.

11. A method according to claim 8 wherein, when said conditional
probability is greater than or equal to said threshold probability
β, said step of determining is repeated until said additional length
of time Δ is maximized.

12. A method according to claim 8 wherein, when said conditional
probability is less than said threshold probability β, said method
further comprises the step of setting said one of said future silence
periods equal to said computed training silence length of time α.

13. A system for conserving battery power in a battery-powered
communication device that supports a conversation over a wireless network
transport media, comprising a controller adapted to be included in a
battery-powered communication device capable of supporting a conversation
over a wireless network transport media, the communication device having
a high power state (HPS) of operation and a low power state (LPS) of
operation wherein battery power required for said LPS is less than
battery power required for said HPS, said controller detecting periods of
silence during at least a portion of at least one conversation supported
by the communication device, said controller predicting, using said
periods of silence so-detected, future silence periods occurring during
at least one of (i) a remainder of said at least one conversation, and
(ii) a future conversation supported by the communication device, and
said controller placing the communication device in said LPS during each
of said future silence periods so-predicted.

14. A system as in claim 13 wherein, when said portion of at least one
conversation is in the form of digitized samples thereof, said controller
detects said periods of silence by comparing a threshold audio level to
an average audio level associated with a portion of said digitized
samples, wherein one of said periods of silence is indicated each time
said average audio level is less than said threshold audio level.

15. A system as in claim 13, wherein said controller predicts said future
silence periods by generating an empirical cumulative distribution
function (ECDF) using said periods of silence so-detected, generating a
computed training silence length of time α using said ECDF;
detecting a current silence period occurring during one of (i) said
remainder of said at least one conversation, and (ii) said future
conversation; and determining, using said ECDF, a conditional probability
that said current silence period will last an additional length of time
Δ beyond said computed training silence length of time α,
wherein one of said future silence periods is defined by
(α+Δ) when said conditional probability is greater than or
equal to a threshold probability β.

16. A system as in claim 15, wherein said threshold probability β is
in the range of approximately 0.25 to approximately 0.7.

17. A system as in claim 15 wherein, when said conditional probability is
greater than or equal to said threshold probability β, said
controller continues determining said conditional probability until said
additional length of time Δ is maximized.

18. A system as in claim 15 wherein, when said conditional probability is
less than said threshold probability β, said controller sets said
one of said future silence periods equal to said computed training
silence length of time α.

19. A method of conserving network resources, comprising the steps of:
detecting periods of silence during at least a portion of at least one
conversation adapted to take place on a network having controllable
resources; predicting, using said periods of silence so-detected, future
silence periods occurring on the network; and controlling allocation of
at least a portion of the controllable resources based on said future
silence periods.

20. A method according to claim 19, wherein said step of predicting
comprises the steps of: generating an empirical cumulative distribution
function (ECDF) using said periods of silence so-detected; generating a
computed training silence length of time α using said ECDF;
detecting a current silence period occurring on the network; and
determining, using said ECDF, a conditional probability that said current
silence period will last an additional length of time Δ beyond said
computed training silence length of time α, wherein one of said
future silence periods is defined by (α+Δ) when said
conditional probability is greater than or equal to a threshold
probability β.

21. A method according to claim 20, wherein said threshold probability
β is in the range of approximately 0.25 to approximately 0.7.

22. A method according to claim 20 wherein, when said conditional
probability is greater than or equal to said threshold probability
β, said step of determining is repeated until said additional length
of time Δ is maximized.

23. A method according to claim 20 wherein, when said conditional
probability is less than said threshold probability β, said method
further comprises the step of setting said one of said future silence
periods equal to said computed training silence length of time α.

Description:

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] Not applicable.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT

[0002] Not applicable.

FIELD OF INVENTION

[0003] The field of the invention relates generally to network resource
conservation methods and systems, and more particularly to a method and
system for conserving a resource such as battery power used by a
communication device during conversations carried on over wireless
network transport media.

BACKGROUND OF THE INVENTION

[0004] Many of today's two-party or multiple-party conversations are
accomplished using some sort of wireless communication system such as the
cellular data network or a wireless network transport media (e.g., WiFi,
2 G, 3 G, 4 G, etc.). In either case, a battery powered communication
device (e.g., cell phone, smart phone, laptop computer, etc.) is
typically used to access the wireless communication system. In terms of
battery power requirements, communication devices use less battery power
when accessing the cellular data network than when accessing one of the
wireless network transport media. However, wireless network transport
media provide (i) faster data transfer rates than the cellular data
network, (ii) lower costs of usage since the airtime charges associated
with the cellular data network do not typically apply, and (iii) lower
latency compared to the cellular data network. Balancing these pros and
cons of the cellular data network versus a wireless network transport
media, more and more users of wireless communication device users are
electing to use a wireless network transport media to carry on a wireless
conversation.

[0005] The vast majority of battery-powered communication devices using a
wireless network transport media can be classified as smart phones. As
much as one-third of a smart phone's battery energy is consumed by its
interface that accesses a wireless network transport media. That is, when
this interface is "on" (i.e., fully powered in the case of 2 G/3 G/4 G)
or "awake" (i.e., powered to support the device's Constantly Awake Mode
(CAM) in the case of WiFi), the power requirements are substantially
greater than when this interface is "off" (i.e., no power in the case of
2 G/3 G/4 G) or "asleep" (i.e., minimally powered to support the device's
Power Save Mode (PSM) in the case of WiFi). Accordingly, it is important
to "power" this interface only when necessary to conserve battery power
for the communication device.

[0006] Studies have shown that periods of silence (i.e., no conversation
audio from any party) comprise up to 60% of a typical human conversation.
If a smart phone is "on" or in CAM during these periods of silence, the
phone's interface is wasting battery power since data "blanks" are being
sent/received over the wireless network transport media. It is clear that
substantial battery power savings could be achieved if a smart phone's
wireless network transport media interface was "off" or in PSM during
most or all of the periods of silence. In the current state-of-the-art,
most smart phones use a technique referred to as "adaptive PSM" to
attempt to exploit the periods of silence in a conversation to save
battery power. Briefly, adaptive PSM saves battery power by defaulting
the smart phone to PSM and switching to CAM when traffic is observed on
the wireless local area network (WLAN) being accessed. One drawback of
adaptive PSM is that the transition time delay associated with mode
switching (i.e., approximately 1.5 seconds) negatively impacts phone
performance when periods of silence are small or when traffic arrives in
clumps or bursts. A detailed description of adaptive PSM is presented by
E. Rozner et al. in "Network-Assisted Power Management for WiFi Devices,"
The Annual International Conference on Mobile Systems, Applications, and
Services, 2010.

BRIEF SUMMARY OF THE INVENTION

[0007] Accordingly, it is an object of the present invention to provide a
battery-powered communication device with a method and system for
conserving battery power when the communication device is used to support
a conversation over a wireless network transport media.

[0008] Another object of the present invention is to provide a method and
system for exploiting periods of silence in a conversation to conserve
battery power for a battery-powered communication device.

[0009] In accordance with the present invention, a method and system are
provided for conserving network resources such as battery power of a
battery-powered communication device used to support a conversation over
a wireless network transport media. Periods of silence are detected
during at least a portion of at least one conversation taking place on a
network having controllable resources such as battery power. Using the
periods of silence so-detected, future silence periods occurring on the
network are then predicted. Allocation of at least a portion of the
controllable resources is controlled based on the future silence periods
so-predicted.

BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The summary above, and the following detailed description, will be
better understood in view of the drawings that depict details of
preferred embodiments.

[0011] The sole FIGURE is a top-level block diagram of an architecture
used in implementing silence prediction-based battery power conservation
in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

[0012] The present invention is a novel approach to conserving network
resources when that network could be transmitting periods of "silence" or
no data. In one embodiment of the present invention, conserving network
resources means saving battery power for a battery-powered communication
device supporting a conversation over a wireless network transport media.
In this embodiment, the communications device becomes part of a network
during a conversation. However, as will be explained later herein, the
present invention could be used for other network resource conservation
applications.

[0013] Before describing an exemplary embodiment of the present invention,
it will be useful to describe and define the terms "communication
device," "conversation" and "wireless network transport media", as they
will be referred to herein in order to illustrate the scope of the
present invention. The term "communication device" refers to any phone,
smart phone, personal computer, laptop computer, video game console, or
other device that can connect to the internet using a wireless network
transport media and support a human conversation thereover. The term
"wireless network transport media" refers to any of a range of
technologies that can provide a communication device with access to the
internet in a wireless fashion so that a conversation can be supported
thereover. Examples of well-known wireless network media include those
based on the Institute of Electrical and Electronic Engineers (IEEE)
802.11 standards (more commonly referred to by the trademark "WiFi" or
derivative terms thereof). Other examples of wireless network transport
media include the multiple generations (i.e., "2 G," "3 G," "4 G," etc.)
based on the standards/specifications set forth by the International
Telecommunications Union in the International Mobile Telecommunications
(IMT)-2000 (or IMT-2000 as it is known).

[0014] In the present invention, a communication device's battery power is
conserved or saved during periods of silence that occur during the course
of human conversation. These periods of silence are periods of mutual
silence, i.e., no words/sounds are being spoken/made by any party to the
conversation. They can occur during the course of one person's
sentence/thought, or can occur as one person waits for a response from
another person. A period of silence as referred to herein can be some
minimal silence period predicated on the responsiveness of the network
medium (e.g., WiFi response time to switch between its Power Save Mode
(PSM) and Constantly Awake Mode (CAM) is on the order of milliseconds but
future technologies may provide faster response times on the order of
microseconds). A period of silence as referred to herein can also last
for several seconds or more.

[0015] As mentioned previously herein, periods of silence (or silence
periods) occupy up to 60% or more of the time between the beginning and
end of a typical human conversation. The present invention exploits this
condition to save battery power during such silence periods while
maintaining the integrity of the conversation. Battery power savings are
achieved by placing a communication device in a low power state during
much or most of a conversation's silence periods. A low power state is
defined as a communication device's state of lower energy requirements
(e.g., power needed to keep the device's wireless network transport
media's interface inactive or asleep) as compared to the device's state
of higher energy requirements (e.g., power needed to keep the device's
wireless network transport media's interface actively communicating with
the internet). The specifics of a communication device's low/high power
states can vary without departing from the scope of the present
invention. For example, in WiFi-enabled devices, the low power state uses
a small amount of battery power and is referred to as the Power Save Mode
(PSM), and the high power state is referred to as the Constantly Awake
Mode (CAM). In 2 G/3 G/4 G-enabled devices, the low power state uses
approximately zero battery power and the high power state uses some
greater amount of battery power.

[0016] A description of the present invention provided herein will be
referenced to conversation "data" that is digitized/packetized at a
sender's device and then re-assembled at a receiver's device. As is known
in the art, real-time protocol (RTP) packets are usually sent/transmitted
at evenly-spaced intervals decided upon by the communication devices used
to carry on a conversation. During silence periods, an RTP packet is
completely empty, i.e., no meaningful data contained therein. While this
type of digitized/packetized conversation data transmission scheme is
used in such ubiquitous schemes as "voice over internet protocol" (VoIP),
the present invention is not limited to use therewith. For example, the
present invention could also be used with digital cellular networks such
as GSM, TDMA and CDMA. Further, when a conversation is transmitted
between a mobile station and a base substation, it may also be possible
to place the radio into a low power state during silence periods.

[0017] Referring now to the sole FIGURE, an architecture used in the
implementation of silence prediction-based battery power conservation in
accordance with an embodiment of the present invention is illustrated. In
the illustrated embodiment, two communication devices 100 and 200 are
used to carry on a conversation over the internet 300. Communication
device 100 is illustrated with the modules/components associated with the
present invention as well as those relevant to the description of the
present invention. Communication device 200 can be, but need not be,
equipped similar to communication device 100. Accordingly, only the
details of device 100 will be described herein to provide an
understanding of the present invention. Communication device 200 is
assumed to be remotely-located with respect to device 100 where the term
"remote" is understood to include very short distances (on the order of
feet) to very large distances (on the order of hundreds to thousands of
miles). It is further assumed that one party/person will use device 100
to converse with another party/person using device 200. Thus, the
illustrated embodiment supports a two-party conversation. However, it is
to be understood that the approach described herein applies equally as
well to multiple-party conversations using additional communication
devices or multiple parties sharing a communication device.

[0018] Communication device 100 includes a battery 102 used to supply
power to the various components of device 100 as would be understood in
the art. Therefore, for clarity of illustration, power supply "lines"
coupling battery 102 to the various components of device 100 have been
omitted. Further, the type of battery 102 used by device 100 is not a
limitation of the present invention.

[0019] In the illustrated embodiment, it is assumed that device 100 sends
and receives packets of digitized conversation "data" in accordance with
real-time protocol (RTP) standards. Accordingly, device 100 includes an
RTP module 104 that receives RTP packets over internet 300 and sends RTP
packets to internet 300. For conversation reception, RTP module 104
reassembles the packets in a playback buffer 106 which, in turn, provides
the re-assembled packets as digital or analog signal to an audio output
device 108 (e.g., a speaker). For conversation transmission, an audio
input device 110 (e.g., a microphone) is coupled to a buffer 112 where
conversation data is digitized prior to processing by the present
invention. Such digitization of conversation is well understood in the
art.

[0020] The present invention introduces two new modules/components 114 and
116 to device 100 in order to carry out a novel method of conserving
battery power for device 100. Silence detection module 114 and silence
prediction module 116 can be separate modules/components or can be
incorporated into a single module/component (e.g., controller, processor,
etc.) without departing from the scope of the present invention. These
modules "listen" to the conversation passing through RTP module 104 in
order to control the power state of battery 102. Very generally, these
modules cooperate to predict the duration of future silence periods based
on previous conversation history and a conditional probability function.
The predictions are then used to place the device's internet interface
118 (e.g., WiFi driver in WiFi-enabled devices, the cellular radio in 2
G/3 G/4 G enabled devices) in its low power state (e.g., PSM for
WiFi-enabled devices, "off" for 2 G/3 G/4 G-enabled devices) during the
predicted future silence periods where little or no power is required
from battery 102.

[0021] The method implemented by modules 114 and 116 includes a training
time operation and a run-time operation. Since a user of device 100 will
have a unique but generally patterned style of conversation, the present
invention includes a training time for collecting data indicative of the
user's unique speech style. In the present invention, a training time can
span a portion of a single conversation, an entire single conversation,
the entirety of multiple conversations, etc., without departing from the
scope of the present invention. Accordingly, the present invention could
employ a single training session the very first time device 100 is used,
could employ multiple training sessions over several conversations, or
could employ a training session each time device 100 initiates a
conversation.

[0022] Regardless of the number or length of training times, the approach
used by the present invention is always the same. That is, during
training, silence detection 114 detects silence periods (i.e., periods of
mutual silence) occurring during a conversation over internet 300 using
device 100. Since a goal of the present invention is to conserve battery
power, it is desired to use a simple silence detection scheme having low
processing/power costs associated therewith. By way of example for the
RTP packet embodiment, one approach is to look for RTP packets that
contain no meaningful data as indications of, for example, short silence
periods between two consecutive words in a sentence or a pause in a
conversation. A simple approach to such RTP packet detection is to
examine the amplitude of the audio stream in the RTP packets. More
specifically, the average audio level of the digital samples of an RTP
packet is compared to a preset threshold that is indicative of
conversation silence. When the average audio level is below this
threshold, the RTP packet is classified as silence. Such threshold
determination and setting could be determined in a variety of ways and
could take the sensitivity of device 100 into consideration as would be
well understood in the art. Once the training time is complete, the
present invention enters its run-time phase of operation where the length
of future silence periods is predicted by silence prediction module 116
using the above-described and so-called training silence periods.

[0023] The run-time phase occurs immediately following the training time
phase in a seamless fashion. For example, if training time is to occur
just one time during the beginning of a single conversation or each time
a conversation starts, silence prediction 116 begins as soon as the
pre-determined training time ends. Further, if training is to only occur
one time (or some preset number of times), the training operation will be
bypassed during conversations as silence prediction 116 makes use of the
training silence periods from the earlier-completed training time(s).

[0024] During run-time operation, silence detection 114 observes when a
so-called current silence period begins and silence prediction 116
predicts how long it will last. This prediction is then used by internet
interface 118 to place battery 102 in its low power state for the
predicted length of time. Since the prediction is predicated on training
information specific to the user of device 100, battery power is
conserved in accordance with the speaking tendencies of the user. All of
this takes place without requiring any user input or specific user
operation.

[0025] Silence prediction 116 uses the training silence periods from
silence detection 114 to construct an empirical cumulative distribution
function (ECDF). The ECDF will be unique based on the training data.
Construction of an ECDF is well known in the art. See, for example, D. R.
Cox et al., "Analysis of Survival Data," Chapman & Hall, London, 1984.
The constructed EDCF is first used by silence prediction 116 to determine
what will be referred to herein as a computed training silence length of
time that is based upon the silence periods collected during training as
will be explained in greater detail later herein.

[0026] During run-time operation, silence detection 114 "listens" to the
conversation (e.g., the portion of the conversation commencing at the
conclusion of training, some future conversation when training is not
employed, etc.) to determine when a current silence period has occurred.
Detection of a current silence period can follow the same scheme used
during training or a different scheme without departing from the scope of
the present invention.

[0027] Once a current silence period has been detected, silence prediction
116 employs a conditional probability scheme to predict how long this
current silence period will last. More specifically, prediction in the
present invention uses the ECDF to look for an appropriate incremental
silence length Δ that has a conditional probability
P(X>α+Δ|X>α) larger than or equal to a threshold
probability defined herein as β, where X denotes the length of the
current silence period and a α is the above-referenced computed
training silence length of time that is initially generated from the
ECDF. If an incremental silence length Δ can be found that
satisfies this conditional probability, then the current silence period
is predicted to be equal to (α+Δ). The value of α will
also be updated in accordance with (α+Δ) to prepare for a
possible consecutive prediction. For maximum battery conservation, the
search for a Δ that satisfies the conditional probability can be
repeated in an effort to maximize Δ, thereby maximizing the
predicted length of the current silence period. If an incremental silence
length Δ cannot be found to satisfy this conditional probability,
Δ is set equal to zero such that the current silence period length
prediction of (α+Δ) is essentially the training silence
length of time α. Silence prediction 116 then supplies the
predicted length of time to internet interface 118 for governance of the
low power state of battery 102 as described above. The prediction scheme
continues until the current silence period ends (as detected by silence
detection 114) or until no Δ can be found to satisfy the
conditional probability. The prediction scheme is repeated if the current
silence period is still detected at the end of the predicted length of
time. If the current silence period is no longer detected at the end of
the predicted length of time, battery 102 is restored to its high power
state and silence prediction 116 awaits detection of the next current
silence period.

[0028] While the threshold probability β can generally range from 0
to 1, a variety of test cases of the present invention have shown that
good performance (i.e., battery power conservation) is achieved when the
threshold probability β ranges from approximately 0.25 to
approximately 0.7. Larger values of incremental silence length Δ
are achieved for lower values of β. This results in the greatest
battery power savings. However, this also increases the risk of errors
which can degrade the quality of a phone conversation. Large values of
β improve the conversation quality, but conserve less battery power.
Accordingly, the present invention could provide the user with a "call
quality/battery conservation" input that would allow the user to
essentially select an operational value of β to suit the user's
preference. For example, when a user experiences degradation in
conversation quality (e.g., obvious delay and jitter), conversation
quality could be improved by the user selecting "call quality" to thereby
implement a larger β value. However, when the user wants/needs to
save more battery power, the user could select "battery conservation" to
thereby implement a lower β value.

[0029] Initially, the computed training silence length of time α is
determined to be the minimum α value that satisfies the condition
P(X>α+K|X>α)≧β. Here, the value of β
is set as discussed above. Thus, with a given β value, the minimal
α value is determined for which silence prediction 116 is able to
predict a silence period that is at least K seconds long. The value of K
can be selected to suit a particular application. For example, in the
case of VoIP using RTP packets, K could be 20 milliseconds because this
is the time it takes for VoIP to generate one RTP packet.

[0030] The advantages of the present invention are numerous. Silence
period prediction in a phone conversation is used to conserve battery
power without negatively impacting call quality. In tests of the present
invention using various types of training data and a variety of threshold
probability values, the present invention achieved energy savings of 40%
or more during a phone conversation. This will extend the life of a
battery charge for users of a variety of communication devices using the
internet to support conversations.

[0031] As mentioned above, the present invention can be extended to other
network resource conservation applications. For example, the owner of a
packet switching network or circuit switching network could also take
advantage of the above-described future silence prediction. In packet
switching, a VoIP application running through a Multi-Protocol Label
Switching (MPLS) virtual link could take advantage of the silence
prediction by freeing up resources during the silence periods for other
purposes by, for instance, not tagging silence packets or setting the
silence packets to a lower priority in terms of resource allocation. If
the network provider sees significant VoIP traffic, the amount of network
resources saved (or made available for other functions) during this
period could be significant since roughly 60% of voice traffic can be
classified as silence. For a circuit switched network with dedicated
voice trunks, resources could be saved by silence prediction in the
following manner. During predicted silence periods, the voice trunks
could be used for other purposes for short "bursty" traffic. For
instance, a voice circuit could be reassigned to send "short message
service" (SMS) traffic during a silence period that is long enough.

INCORPORATION BY REFERENCE

[0032] All publications, patents, and patent applications cited herein are
hereby expressly incorporated by reference in their entirety and for all
purposes to the same extent as if each was so individually denoted.

EQUIVALENTS

[0033] While specific embodiments of the subject invention have been
discussed, the above specification is illustrative and not restrictive.
Many variations of the invention will become apparent to those skilled in
the art upon review of this specification. Thus, the full scope of the
invention should be determined by reference to the claims, along with
their full scope of equivalents, and the specification, along with such
variations.

Patent applications by Andrew J. Pyles, Williamsburg, VA US

Patent applications by Gang Zhou, Williamsburg, VA US

Patent applications by COLLEGE OF WILLIAM AND MARY

Patent applications in class Signaling for performing battery saving

Patent applications in all subclasses Signaling for performing battery saving